SOTAVerified

Dimensionality Reduction

Dimensionality reduction is the task of reducing the dimensionality of a dataset.

( Image credit: openTSNE )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 41–50 of 3304 papers

TitleStatusHype
Deep Domain Adaptation: A Sim2Real Neural Approach for Improving Eye-Tracking SystemsCode1
GCN-DevLSTM: Path Development for Skeleton-Based Action RecognitionCode1
Light Curve Classification with DistClassiPy: a new distance-based classifierCode1
A new computationally efficient algorithm to solve Feature Selection for Functional Data Classification in high-dimensional spacesCode1
Linear Recursive Feature Machines provably recover low-rank matricesCode1
FILP-3D: Enhancing 3D Few-shot Class-incremental Learning with Pre-trained Vision-Language ModelsCode1
Symplectic Autoencoders for Model Reduction of Hamiltonian SystemsCode1
Metric Space Magnitude for Evaluating the Diversity of Latent RepresentationsCode1
Learning Arousal-Valence Representation from Categorical Emotion Labels of SpeechCode1
Spectral Clustering of Attributed Multi-relational GraphsCode1
Show:102550
← PrevPage 5 of 331Next →
All datasetsMCAEMNIST

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy90.9—Unverified
2tSNEClassification Accuracy51.5—Unverified
3IVISClassification Accuracy46.6—Unverified
4UMAPClassification Accuracy41.3—Unverified
#ModelMetricClaimedVerifiedStatus
1UDRNClassification Accuracy71.1—Unverified
2QSClassification Accuracy68—Unverified